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Introduction to NLP • What is NLP? • Definition and significance • Key areas: text processing, sentiment analysis, language understanding
Azure Cognitive Services for NLP • Overview of Azure Cognitive Services • Text Analytics, Language Understanding (LUIS), Translator, Speech services
Text Analytics API • Features and Capabilities • Sentiment analysis • Key phrase extraction • Named entity recognition • Language detection
Language Understanding (LUIS) • Building Custom Language Models • Intent recognition • Entity extraction • Example use cases: catboats, virtual assistants
Translator Service • Real-Time Language Translation • Supported languages • Use cases: multilingual support, real-time communication
Speech to Text and Text to Speech • Integrating Speech with NLP • Speech recognition (converting spoken language to text) • Speech synthesis (converting text to spoken language)
Practical Applications of NLP in Azure • Industry Use Cases • Customer support automation • Content moderation and analysis • Sentiment analysis for social media monitoring
Conclusion and Future Directions Summary of Key Points Azure's comprehensive NLP capabilities Growing importance of NLP in various industries Future advancements and AI trends
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